Abstract

Background

DNA-based predictions for hard-to-measure production traits hold great promise for selective breeding programs. DNA pooling might provide a cheap genomic approach to use phenotype data from commercial flocks which are commonly group-mated with parentage unknown. This study on sheep explores if genomic breeding values for stud sires can be estimated from genomic relationships that were obtained from pooled DNA in combination with phenotypes from commercial progeny.

Methods

Phenotypes used in this study were categorical data. Blood was pooled strategically aiming at even pool sizes and within sex and phenotype category. A hybrid genomic relationship matrix was constructed relating pools to sires. This matrix was used to determine the contribution of sires to each of the pools and therefore phenotype category by using a simple regression approach. Genomic breeding values were also estimated using the hybrid genomic relationship matrix.

Results

We demonstrated that, using pooled DNA, the genetic performance of sires can be illustrated as their contribution to phenotype categories and can be expressed as a regression coefficient. Genomic estimated breeding values for sires were equivalent to the regression coefficients and are a commonly used industry tool.

Conclusions

Genotyping of DNA from pooled biological samples offers a cheap method to link phenotypic information from commercial production animals to the breeding population and can be turned into information on the genetic value of stud sires for traits that cannot be measured in the stud environment.

Details

Title
Estimating the genetic merit of sires by using pooled DNA from progeny of undetermined pedigree
Author
Bell, Amy M; Henshall, John M; Porto-Neto, Laercio R; Dominik, Sonja; McCulloch, Russell; Kijas, James; Lehnert, Sigrid A
Pages
1-7
Section
Research Article
Publication year
2017
Publication date
2017
Publisher
Springer Nature B.V.
ISSN
0999193X
e-ISSN
12979686
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2575277402
Copyright
© 2017. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.